As an application testing expert with over 10 years of experience validating software on 3500+ real mobile and desktop devices, I’ve seen firsthand the game-changing impact continuous testing can provide.
When leveraged effectively, automatically executing tests in parallel with development significantly raises code quality and accelerates delivery speed.
In this comprehensive guide, we’ll cover what continuous testing is, why it’s essential for DevOps, who benefits, and how to integrate it optimally into your workflow.
What is Continuous Testing and Why it Matters
Continuous testing refers to automatically testing each code change committed by developers early in the software lifecycle. Tests are executed against every commit to provide rapid feedback on whether new code breaks or conflicts with existing functionality.
By testing incrementally, defects can be detected shortly after being introduced while developer context remains fresh. This allows bugs and regressions to be fixed faster, reducing cost and risk.
Research by IBM suggests software defects that reach production are 15-50 times more expensive to fix than if caught during development. Continuous testing drives down escaped defect rates substantially.
The Critical Role of Continuous Testing in DevOps
Continuous testing dovetails perfectly with core DevOps principles:
- Frequent software releases – Testing every commit maintains quality needed to release often
- Rapid feedback loops – Automated checks after each merge provide fast feedback on changes
- Shared responsibility – Devs own testing code as they author features; QA facilitates executable specs
By incorporating continuous testing, DevOps teams can:
- Release features faster thanks to incremental validation
- Maintain velocity by preventing quality erosion over time
- Avoid costly hot fixes and app downtime from undetected defects
These benefits explain the 92% higher change success rate for teams doing continuous testing based on research by Capgemini.
Who Benefits from Continuous Testing?
Developers, Test Engineers, and Operations Teams all gain immense advantages from continuous testing:
Developers
- Reduce debugging cycles waiting for QA validation
- Fail fast if changes break existing flows early on
- Detect hard-to-diagnose runtime errors through unit testing
- Enable safe refactoring through test coverage
QA Engineers
- Shrink repetitive regression testing cycles
- Focus innovation on customer experience testing
- Leverage API testing to validate endpoints without UI dependency
- Build next-gen frameworks like shift-left that unit tests anchor
Ops Engineers
- Higher app stability via incremental validation
- Less unplanned work from pre-production bugs
- Advance AIOps by integrating code quality checks
- Construct safety nets ensuring site reliability
The data shows that 60% of teams using continuous testing have enhanced collaboration between Dev, QA and Ops. The feedback loop tightens communication and increases empathy between roles.
Best Practices for Adopting Continuous Testing
Based on my decade of experience helping clients implement continuous validation strategies, here are five recommendations:
1. Phase Your Approach
Don’t attempt to revamp your entire testing process at once. This will likely overwhelm your staff. Instead, roll out incrementally:
Phase 1: Add CI-triggered unit tests
Phase 2: Expand to API testing of services
Phase 3: Incorporate automated UI tests
Measure as you go and adapt based on feedback. Consistently evangelize wins to build further mindshare.
2. Start Testing Early
To maximize advantage, begin authoring test cases while initially building features – not after claiming code complete.
Consider test design even before you code by defining key scenarios in Gherkin/Cucumber. These will form the backbone of test automation scripts later.
Early involvement reduces dependency on manual testing cycles for validation. You uncover more issues faster through automation.
3. Incentivize Test Creation
Recognize developers who author clean, testable code. If they feel accountable only for delivering features quickly – testing will be an afterthought.
Display test coverage metrics on dashboards. This visibility motivates authors to increase numbers.
Drive competition through gamification by awarding badges for contributions like new test cases added.
4. Monitor Overall Quality
While individual test pass/fail signals problems, also instrument overall quality with code analysis tools:
- Technical Debt – Flags building issues requiring eventual refactor
- Code Coverage % – Measures extent of test inclusion
- Anti-Pattern Detection – Identify poor development practices to avoid
- Cyclomatic Complexity – Highlights code difficult to test/maintain
Robust analytics provide holistic insights to focus improvement efforts.
5. Respond Rapidly to Failures
When tests fail, have a defined protocol for investigation:
- Rotate investigating failures between team members
- Reproduce errors quickly before details fade
- Identify root cause not just symptoms
- File bugs linking to failing tests as foundation of diagnoses
Prioritizing test repair builds accountability. It also surfaces holes in test practices needing strengthened.
By following these continuous testing best practices, you will propel stability, speed up release cycles, reduce costs, and make customers happier.
Choosing Continuous Testing Tools
With a sound strategy in place, the next step is determining tooling that aligns to your tech stack and use cases. Here are top considerations when evaluating test automation solutions:
Test Authoring Frameworks
These libraries allow writing resilient test cases covering:
- Unit Testing – Validates discrete code components and functions
- API Testing – Confirms services return expected responses
- UI Testing – Interacts with rendered user interfaces
Open source options like Selenium and Cypress excel across browser and API testing. JUnit, NUnit, and xUnit lead in unit testing.
When assessing options, prioritize ease of use, reuse, reporting, and debugging. Also consider framework maturity and community size.
Continuous Integration (CI) Servers
CI platforms connect to source control to auto-build applications and execute tests in response to commits. They provide the backbone of DevOps pipelines.
Jenkins stands as the leading open source CI server – extended via 1500+ plugins. CircleCI and Travis CI offer robust SaaS alternatives.
Evaluate CI tools across integration breadth, parallelization, security posture, scalability, and ease of configuration. Open source options have more customization while SaaS delivers better time-to-value.
I suggest piloting both Jenkins and a SaaS platform like CircleCI to determine the right balance of flexibility and convenience for your needs.
Cloud Testing Environments
Running tests directly within CI tools has scalability and consistency challenges:
✔️ Dynamically spinning up complex test environments is hard
✔️ Tests contend for resources with builds slowing everything down
✔️ Limited access to comprehensive test analytics
That’s why leading teams complement their CI solution with a cloud testing platform:
These testing clouds stand up production-like environments on-demand while offering debugging tools, video recordings, advanced reporting, and more.
Based on 10 years of comparative analysis, I recommend either BrowserStack or LambdaTest depending upon specific feature needs. Both enable simplified management of test infrastructure and data-driven decision making.
Overcoming Continuous Testing Challenges
Adopting continuous testing involves more than just tools. Scaling adoption requires addressing common people and process obstacles like:
Cultural Resistance
Developers often view testing as a burden infringing upon their coding time. It helps to incentivize writing testable code as you ramp up automation engineering.
Consider tying test coverage percentage to performance scores for devs. Also rotate test failure remediation duties between all team members.
Shared responsibility builds empathy while exposing testing gaps at the code level.
Legacy Systems
Monolithic apps with lots of technical debt often lack isolated components needed for unit testing. Begin instead with API testing integration points between modern microservices.
Use strangler pattern migrations to slowly decompose bigger applications over time. This incrementally unlocks testability.
Measuring Coverage
Targeting 100% coverage across unit, integration, and UI testing is unrealistic starting out. Prioritize validation of key user journeys end-to-end first.
Analyze usage data to determine high risk areas based on usage patterns. Expand test writing to cover these areas earlier.
Review coverage improvement in failure prone zones weekly until saturation reached.
Realize the Full Potential of Continuous Testing
As I‘ve validated firsthand through my consulting engagements, baked-in continuous testing drives tremendous value.
But overcoming inertia requires education on benefits, designing the optimal strategy, selecting the right supporting tools, and addressing organizational obstacles.
By following the recommendations in this guide, your team can actualize huge productivity and quality advantages. The outcome is reliably releasing secure, resilient software at velocity.
Now over to you – what questions do you have on continuous testing in DevOps? I‘m happy to offer specific recommendations based on your objectives and constraints.
